Search results for: niche fitness evaluation model

Authors: Daniela Salih Khidir, Mohamed G. Al Kuwari, Mercia V. Walt, Izzeldin J. Ibrahim

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Background: University-based physical activity interventions aim to establish durable social patterns during the transition to adulthood. This study is a comprehensive evaluation of a 3-year intervention-based program to increase the culture of physical activity (PA) routine in Qatar campuses community, using a holistic approach. Methodology: General assessment methods: formative evaluation-SIH Campuses logic model design, stakeholders’ identification; process evaluation-members’ step counts analyze and qualitative Appreciative Inquiry session (4-D model); daily steps categorized as: ≤5,000, inactive; 5,000-7,499 low active; ≥7,500, physically active; outcome evaluation - records 3 years interventions. Holistic PA interventions methods: walking interventions - pedometers distributions and walking competitions for students and staff; educational interventions - in campuses implementation of bilingual educational materials, lectures, video related to PA in prevention of non-communicable diseases (NCD); articles published online; monthly emails and sms notifications for pedometer use; mass media campaign - radio advertising, yearly pre/post press releases; community stakeholders interventions-biyearly planning/reporting/achievements rewarding/ qualitative meetings; continuous follow-up communication, biweekly steps reports. Findings: Results formative evaluation - SIH in Campuses logic model identified the need of PA awareness and education within universities, resources, activities, health benefits, program continuity. Results process evaluation: walking interventions: Phase 1: 5 universities recruited, 2352 members, 3 months competition; Phase 2: 6 new universities recruited, 1328 members in addition, 4 months competition; Phase 3: 4 new universities recruited in addition, 1210 members, 6 months competition. Results phase 1 and 2: 1,299 members eligible for analyzes: 800 females (62%), 499 males (38%); 86% non-Qataris, 14% Qatari nationals, daily step count 5,681 steps, age groups 18–24 (n=841; 68%) students, 25–64; (n=458; 35.3%) staff; 38% - low active, 37% physically active and 25% inactive. The AI main themes engaging stakeholders: awareness/education - 5 points (100%); competition, multi levels of involvement in SIH, community-based program/motivation - 4 points each (80%). The AI points represent themes’ repetition within stakeholders’ discussions. Results education interventions: 2 videos implementation, 35 000 educational materials, 3 online articles, 11 walking benefits lectures, 40 emails and sms notifications. Results community stakeholders’ interventions: 6 stakeholders meetings, 3 rewarding gatherings, 1 focus meeting, 40 individual reports, 18 overall reports. Results mass media campaign: 1 radio campaign, 7 press releases, 52 campuses newsletters. Results outcome evaluation: overall 2013-2016, the study used: 1 logic model, 3 PA holistic interventions, partnerships 15 universities, registered 4890 students and staff (aged 18-64 years), engaged 30 campuses stakeholders and 14 internal stakeholders; Total registered population: 61.5% female (2999), 38.5% male (1891), 20.2% (988) Qatari nationals, 79.8% (3902) non-Qataris, 55.5% (2710) students aged 18 – 25 years, 44.5% (2180) staff aged 26 - 64 years. Overall campaign 1,558 members eligible for analyzes: daily step count 7,923; 37% - low active, 43% physically active and 20% inactive. Conclusion: The study outcomes confirm program effectiveness and engagement of young campuses community, specifically female, in PA. The authors recommend implementations of 'holistic PA intervention program approach in Qatar' aiming to impact the community at national level for PA guidelines achievement in support of NCD prevention.

Keywords: campuses, evaluation, Qatar, step-count

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Authors: Yogita Weikey, Shobha Lata Sinha, Satish Kumar Dewangan

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In the present investigation, rheology of the three different natural gums has been evaluated experimentally using MCR 102 rheometer. Various samples based on the variation of the concentration of the solid gum powder have been prepared. Their non-Newtonian behavior has been observed by the consistency plots and viscosity variation plots with respect to different solid concentration. The viscosity-shear rate curves of gums are similar and the behavior is shear thinning. Gums are showing pseudoplastic behavior. The value of k and n are calculated by using various models. Results show that the Herschel–Bulkley rheological model is reliable to describe the relationship of shear stress as a function of shear rate. R² values are also calculated to support the choice of gum selection.

Keywords: bentonite, Indian gum, non-Newtonian model, rheology

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Authors: Bello Abdullahi, Yahaya M. Ibrahim, Ahmed D. Ibrahim, Kabir Bala

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Public sector tendering has traditionally been conducted using manual paper-based processes which are known to be inefficient, less transparent and more prone to manipulations and errors. The advent of the Internet and the World Wide Web has led to the development of numerous e-Tendering systems that addressed some of the problems associated with the manual paper-based tendering system. However, most of these systems rarely support the evaluation of tenders and where they do it is mostly based on the single decision maker which is not suitable in public sector tendering, where for the sake of objectivity, transparency, and fairness, it is required that the evaluation is conducted through a tender evaluation committee. Currently, in Nigeria, the public tendering process in general and the evaluation of tenders, in particular, are largely conducted using manual paper-based processes. Automating these manual-based processes to digital-based processes can help in enhancing the proficiency of public sector tendering in Nigeria. This paper is part of a larger study to develop an electronic tendering system that supports the whole tendering lifecycle based on Nigerian procurement law. Specifically, this paper presents the design and implementation of part of the system that supports group evaluation of tenders based on a technique called fuzzy multi-attributes group decision making. The system was developed using Object-Oriented methodologies and Unified Modelling Language and hypothetically applied in the evaluation of technical and financial proposals submitted by bidders. The system was validated by professionals with extensive experiences in public sector procurement. The results of the validation showed that the system called NPS-eTender has an average rating of 74% with respect to correct and accurate modelling of the existing manual tendering domain and an average rating of 67.6% with respect to its potential to enhance the proficiency of public sector tendering in Nigeria. Thus, based on the results of the validation, the automation of the evaluation process to support tender evaluation committee is achievable and can lead to a more proficient public sector tendering system.

Keywords: e-Tendering, e-Procurement, group decision making, tender evaluation, tender evaluation committee, UML, object-oriented methodologies, system development

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Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

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Authors: Guilherme Gorgulho, Carlos Roberto Camello Lima

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Critical success factors (CSF) are used to design the practice of project management that can lead directly or indirectly to the success of the project. This management includes many elements that have to be synchronized in order to ensure the project on-time delivery, quality and the lowest possible cost. The objective of this work is to develop a proposal for evaluation of the FCS in lean manufacturing projects, and apply the evaluation in a pilot project. The results show that the use of continuous improvement programs in organizations brings benefits as the process cost reduction and improve productivity.

Keywords: continuous improvement, critical success factors (csf), lean thinking, project management

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Authors: Eleanor Nel

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Research output is an indicator of institutional performance (and quality), resulting in increased pressure on academic institutions to perform in the research arena. Research output is further utilised to obtain research funding. Resultantly, academic institutions face significant pressure from governing bodies to provide evidence on the return for research investments. Research output has thus become a substantial discourse within institutions, mainly due to the processes linked to evaluating research output and the associated allocation of research funding. This focus on research outputs often surpasses the development of robust, widely accepted tools to additionally measure research impact at institutions. A publication writing programme, for enhancing research output, was launched at a South African university in 2011. Significant amounts of time, money, and energy have since been invested in the programme. Although participants provided feedback after each session, no formal review was conducted to evaluate the research output directly associated with the programme. Concerns in higher education about training costs, learning results, and the effect on society have increased the focus on value for money and the need to improve training, research performance, and productivity. Furthermore, universities rely on efficient and reliable monitoring and evaluation systems, in addition to the need to demonstrate accountability. While publishing does not occur immediately, achieving a return on investment from the intervention is critical. A multi-method study, guided by the New World Kirkpatrick Model (NWKM), was conducted to determine the impact of the publication writing programme for the period of 2011 to 2018. Quantitative results indicated a total of 314 academics participating in 72 workshops over the study period. To better understand the quantitative results, an open-ended questionnaire and semi-structured interviews were conducted with nine participants from a particular faculty as a convenience sample. The purpose of the research was to collect information to develop a comprehensive framework for impact evaluation that could be used to enhance the current design and delivery of the programme. The qualitative findings highlighted the critical role of a multi-stakeholder strategy in strengthening support before, during, and after a publication writing programme to improve the impact and research outputs. Furthermore, monitoring on-the-job learning is critical to ingrain the new skills academics have learned during the writing workshops and to encourage them to be accountable and empowered. The NWKM additionally provided essential pointers on how to link the results more effectively from publication writing programmes to institutional strategic objectives to improve research performance and quality, as well as what should be included in a comprehensive evaluation framework.

Keywords: evaluation, framework, impact, research output

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Authors: Rithi Baruah

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The aviation industry is one such sectors whose primary aim is to work for the safety and comfort of their clients and customers. The crew members in the aviation industry include pilots, flight attendants, air traffic controllers, baggage personnel and maintenance personnel. This study will concentrate on the frontline employees of the aviation industry, the flight attendants. Flight attendants belong to the niche group of population who are paid to smile. Although the profession seems to be very glamorous, it is physically and psychologically very taxing. Energy at workplace is a fairly new concept and is an organizational resource which helps employee attain their goals. Therefore, the researcher will aim to establish the relationship between relational energy and the major issue of emotional labor and cognitive flexibility among flight attendants. The researcher will hypothesize that there will be a negative relationship between relational energy and emotional labour, and a positive relationship between relational energy and cognitive flexibility. Also, a positive relationship will be expected between cognitive flexibility and emotional labour of cabin crew. A quantitative research design will be used to study the relationship among 50 flight attendants in India. The findings of the research will not only help the aviation sector but will be a major contribution to the existing literature of aviation psychology in India which is scanty. The relationships can also provide scope to develop a model using the same. From crew resource management and aviation psychology perspectives, relationships among the study variables will not only provide scope for helping the aviation employees in particular but also develop the performance and safety of aviation sector at large.

Keywords: cabin crew, cognitive flexibility, emotional labour, relational energy

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Authors: Elmahdi Khalil, Saad Enniari, Mostapha Zbakh

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Cloud computing promises to increase innovation and the velocity with witch applications are deployed, all while helping any enterprise meet most IT service needs at a lower total cost of ownership and higher return investment. As the march of cloud continues, it brings both new opportunities and new security challenges. To take advantages of those opportunities while minimizing risks, we think that Intrusion Detection Systems (IDS) integrated in the cloud is one of the best existing solutions nowadays in the field. The concept of intrusion detection was known since past and was first proposed by a well-known researcher named Anderson in 1980's. Since that time IDS's are evolving. Although, several efforts has been made in the area of Intrusion Detection systems for cloud computing environment, many attacks still prevail. Therefore, the work presented in this paper proposes a multi criteria analysis and a comparative study between several IDS architectures designated to work in a cloud computing environments. To achieve this objective, in the first place we will search in the state of the art of several consistent IDS architectures designed to work in a cloud environment. Whereas, in a second step we will establish the criteria that will be useful for the evaluation of architectures. Later, using the approach of multi criteria decision analysis Mac Beth (Measuring Attractiveness by a Categorical Based Evaluation Technique we will evaluate the criteria and assign to each one the appropriate weight according to their importance in the field of IDS architectures in cloud computing. The last step is to evaluate architectures against the criteria and collecting results of the model constructed in the previous steps.

Keywords: cloud computing, cloud security, intrusion detection/prevention system, multi-criteria decision analysis

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Authors: Anna Ouskova Leonteva, Michel Risser, Anne Jeannin-Girardon, Pierre Parrend, Pierre Collet

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This paper proposes an efficient optimization tool for an active magnetic regenerator (AMR) model, operating in two modes: magnetic refrigeration system (MRS) and thermo-magnetic generator (TMG). The aim of this optimizer is to improve the design of the AMR by applying a multi-physics multi-scales numerical model as a core of evaluation functions to achieve industrial requirements for refrigeration and energy conservation systems. Based on the multi-objective non-dominated sorting genetic algorithm 3 (NSGA3), it maximizes four different objectives: efficiency and power density for MRS and TMG. The main contribution of this work is in the simultaneously application of a CPU-parallel NSGA3 version to the AMR model in both modes for studying impact of control and design parameters on the performance. The parametric study of the optimization results are presented. The main conclusion is that the common (for TMG and MRS modes) optimal parameters can be found by the proposed tool.

Keywords: ecological refrigeration systems, active magnetic regenerator, thermo-magnetic generator, multi-objective evolutionary optimization, industrial optimization problem, real-world application

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Authors: David Gottlieb, Jason Yoder

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The feeling of loneliness is not uncommon in modern society, and yet, there is a fundamental lack of understanding in its origins and purpose in nature. One interpretation of loneliness is that it is a subjective experience that punishes a lack of social behavior, and thus its emergence in human evolution is seemingly tied to the survival of early human tribes. Still, a common counterintuitive response to loneliness is a state of hypervigilance, resulting in social withdrawal, which may appear maladaptive to modern society. So far, no computational model of loneliness’ effect during evolution yet exists; however, agent-based models (ABM) can be used to investigate social behavior, and applying evolution to agents’ behaviors can demonstrate selective advantages for particular behaviors. We propose an ABM where each agent contains four social behaviors, and one goal-seeking behavior, letting evolution select the best behavioral patterns for resource allocation. In our paper, we use an algorithm similar to the boid model to guide the behavior of agents, but expand the set of rules that govern their behavior. While we use cohesion, separation, and alignment for simple social movement, our expanded model adds goal-oriented behavior, which is inspired by particle swarm optimization, such that agents move relative to their personal best position. Since agents are given the ability to form connections by interacting with each other, our final behavior guides agent movement toward its social connections. Finally, we introduce a mechanism to represent a state of loneliness, which engages when an agent's perceived social involvement does not meet its expected social involvement. This enables us to investigate a minimal model of loneliness, and using evolution we attempt to elucidate its value in human survival. Agents are placed in an environment in which they must acquire resources, as their fitness is based on the total resource collected. With these rules in place, we are able to run evolution under various conditions, including resource-rich environments, and when disease is present. Our simulations indicate that there is strong selection pressure for social behavior under circumstances where there is a clear discrepancy between initial resource locations, and against social behavior when disease is present, mirroring hypervigilance. This not only provides an explanation for the emergence of loneliness, but also reflects the diversity of response to loneliness in the real world. In addition, there is evidence of a richness of social behavior when loneliness was present. By introducing just two resource locations, we observed a divergence in social motivation after agents became lonely, where one agent learned to move to the other, who was in a better resource position. The results and ongoing work from this project show that it is possible to glean insight into the evolutionary advantages of even simple mechanisms of loneliness. The model we developed has produced unexpected results and has led to more questions, such as the impact loneliness would have at a larger scale, or the effect of creating a set of rules governing interaction beyond adjacency.

Keywords: agent-based, behavior, evolution, loneliness, social

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Authors: Tomasz L. Nawrocki, Danuta Szwajca

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The growing importance of reputation in building enterprise value and achieving long-term competitive advantage creates the need for its measurement and evaluation for the management purposes (effective reputation and its risk management). The paper presents practical application of self-developed corporate reputation assessment model from the viewpoint of stock market investors. The model has a pioneer character and example analysis performed for selected industry is a form of specific test for this tool. In the proposed solution, three aspects - informational, financial and development, as well as social ones - were considered. It was also assumed that the individual sub-criteria will be based on public sources of information, and as the calculation apparatus, capable of obtaining synthetic final assessment, fuzzy logic will be used. The main reason for developing this model was to fulfill the gap in the scope of synthetic measure of corporate reputation that would provide higher degree of objectivity by relying on "hard" (not from surveys) and publicly available data. It should be also noted that results obtained on the basis of proposed corporate reputation assessment method give possibilities of various internal as well as inter-branch comparisons and analysis of corporate reputation impact.

Keywords: corporate reputation, fuzzy logic, fuzzy model, stock market investors

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Authors: Olumuyiwa Ojo, Masengo Ilunga

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Artificial neural network (ANN) has broken the bounds of the convention programming, which is actually a function of garbage in garbage out by its ability to mimic the human brain. Its ability to adopt, adapt, adjust, evaluate, learn and recognize the relationship, behavior, and pattern of a series of data set administered to it, is tailored after the human reasoning and learning mechanism. Thus, the study aimed at modeling wastewater treatment process in order to accurately diagnose water control problems for effective treatment. For this study, a stage ANN model development and evaluation methodology were employed. The source data analysis stage involved a statistical analysis of the data used in modeling in the model development stage, candidate ANN architecture development and then evaluated using a historical data set. The model was developed using historical data obtained from Daspoort Wastewater Treatment plant South Africa. The resultant designed dimensions and model for wastewater treatment plant provided good results. Parameters considered were temperature, pH value, colour, turbidity, amount of solids and acidity. Others are total hardness, Ca hardness, Mg hardness, and chloride. This enables the ANN to handle and represent more complex problems that conventional programming is incapable of performing.

Keywords: ANN, artificial neural network, wastewater treatment, model, development

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Authors: Manoj Reghu, Prabhu Rajagopal, C. V. Krishnamurthy, Krishnan Balasubramaniam

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A thorough understanding of guided ultrasonic wave behavior in structures is essential for the application of existing Non Destructive Evaluation (NDE) technologies, as well as for the development of new methods. However, the analysis of guided wave phenomena is challenging because of their complex dispersive and multimodal nature. Although numerical solution procedures have proven to be very useful in this regard, the increasing complexity of features and defects to be considered, as well as the desire to improve the accuracy of inspection often imposes a large computational cost. Hybrid models that combine numerical solutions for wave scattering with faster alternative methods for wave propagation have long been considered as a solution to this problem. However usually such models require modification of the base code of the solution procedure. Here we aim to develop Generic Hybrid models that can be directly applied to any two different solution procedures. With this goal in mind, a Numerical Hybrid model and an Analytical-Numerical Hybrid model has been developed. The concept and implementation of these Hybrid models are discussed in this paper.

Keywords: guided ultrasonic waves, Finite Element Method (FEM), Hybrid model

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Authors: Amartya Hatua, Trung Nguyen, Andrew Sung

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In this paper, we study the information diffusion process on Twitter as a multivariate time series problem. Our model concerns three measures (volume, network influence, and sentiment of tweets) based on 10 features, and we collected 27 million tweets to build our information diffusion time series dataset for analysis. Then, different time series clustering techniques with Dynamic Time Warping (DTW) distance were used to identify different patterns of information diffusion. Finally, we built the information diffusion prediction models for new hashtags which comprise two phrases: The first phrase is recognizing the pattern using k-NN with DTW distance; the second phrase is building the forecasting model using the traditional Autoregressive Integrated Moving Average (ARIMA) model and the non-linear recurrent neural network of Long Short-Term Memory (LSTM). Preliminary results of performance evaluation between different forecasting models show that LSTM with clustering information notably outperforms other models. Therefore, our approach can be applied in real-world applications to analyze and predict the information diffusion characteristics of selected topics or memes (hashtags) in Twitter.

Keywords: ARIMA, DTW, information diffusion, LSTM, RNN, time series clustering, time series forecasting, Twitter

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Authors: Mokgophana Ramasobana

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Background: At the core of the demand to utilize evidence-based approaches in the policy-making cycle, prioritization of limited financial resources and results driven initiatives is the urgency to develop a cohort of competent Monitoring and Evaluation (M&E) practitioners and public servants. The ongoing strides in the evaluation capacity building (ECB) initiatives are a direct response to produce the highly-sought after M&E skills. Notwithstanding the rapid growth of M&E short courses, participants perceived value and expectation of M&E short courses as a panacea for ECB have not been empirically quantified or measured. The objective of this article is to explicitly illustrate the importance of measuring ECB interventions and understanding what works in ECB and why it works. Objectives: This article illustrates the importance of establishing empirical ECB measurement tools to evaluate ECB interventions in order to ascertain its contribution to the broader evaluation practice. Method: The study was primarily a desktop review of existing literature, juxtaposed by a survey of the participants across the African continent based on the 43 M&E short courses hosted by the Centre for Learning on Evaluation and Results Anglophone Africa (CLEAR-AA) in collaboration with the Department of Planning Monitoring and Evaluation (DPME) Results: The article established that participants perceive short course training as a panacea to improve their M&E practical skill critical to executing their organizational duties. In tandem, participants are likely to demand customized training as opposed to general topics in Evaluation. However, the organizational environments constrain the application of the newly acquired skills. Conclusion: This article aims to contribute to the 'how to' measure ECB interventions discourse and contribute towards the improvement to evaluate ECB interventions. The study finds that participants prefer training courses with longer duration to cover more topics. At the same time, whilst organizations call for customization of programmes, the study found that individual participants demand knowledge of generic and popular evaluation topics.

Keywords: evaluation capacity building, effectiveness and training, monitoring and evaluation (M&E) short course training, perceptions and expectations

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Authors: Cecilia Estela Jiménez Pérez Campos

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Introduction: Amputation comes from a series of complications in diabetic persons; at that point, of the illness evolution they have a deplored aerobic capacity. Adding to that, cardiac rehabs programs are almost base in several activities in a standing position. The cardiac rehabilitation programs have to improve for them, based on scientific advice. Objective: Evaluation of aerobic capacity of diabetic amputee after an aerobic exercise program, with upper limb ergometer. Methodology: The design is longitudinal, prospective, comparative and no randomized. We include all diabetic pelvic limb amputees, who assist to the cardiac rehabilitation. We made 2 groups: an experimental and a control group. The patients did the exercise testing, with the author’s design protocol. The experimental group completed 24 exercise sessions (3 sessions/week), with an intensity determined with the training heart rate. At the end of 8 weeks period, the subjects did a second exercise test. Results: Both groups were a homogeneous sample in age (experimental n=15) 57.6+12.5 years old and (control n=8) 52.5+8.0 years old, sex, occupation, education and economic features. (square chi) (p=0.28). The initial aerobic capacity was similar in both groups. And the aerobic capacity accomplishes after the program was statistically greater in the experimental group than in the control one. The final media VO2peak (mlO2/kg/min) was experimental (17.1+3.8), control (10.5+3.8), p=0.001. (t student). Conclusions: The aerobic capacity improved after an arm ergometer exercise program and the quality of life improve too, in diabetic amputees. So this program is fundamental in diabetic amputee’s rehabilitation management.

Keywords: aerobic fitness, metabolic equivalent (MET), oxygen output, upper limb ergometer

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Authors: Pavel Zlabek, Vaclav Mentl

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The fatigue crack growth rate evaluation is a basic experimental characteristic when assessment o f the remaining lifetime is needed. Within the repair welding technology project, the crack growth rate at cyclic loading was measured in base and weld metals and in the situation when cracks were initiated in base metal and grew into the weld metal through heat-affected zone and back to the base metal. Two welding technologies were applied and specimens in as-welded state and after heat treatment were tested. Fatigue crack growth rate measurement was performed on CrMoV pressure vessel steel and the tests were performed at room temperature. The crack growth rate was measured on CCT test specimens (see figure) for both the base and weld metals and also in the case of crack subsequent transition through all the weld zones. A 500 kN MTS controlled electro-hydraulic testing machine and Model 632.13C-20 MTS extensometer were used to perform the tests.

Keywords: cracks, fatigue, steels, weldments

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Authors: Yuan-Jye Tseng, Ching-Yen Chen

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In the design cycle, a main design task is to determine the external shape of the product. The external shape of a product is one of the key factors that can affect the customers’ preferences linking to the motivation to buy the product, especially in the case of a consumer electronic product such as a mobile phone. The relationship between the external shape and the customer preferences needs to be studied to enhance the customer’s purchase desire and action. In this research, a design for customer preferences model is developed for investigating the relationships between the external shape and the customer preferences of a product. In the first stage, the names of the geometric features are collected and evaluated from the data of the specified internet web pages using the developed text miner. The key geometric features can be determined if the number of occurrence on the web pages is relatively high. For each key geometric feature, the numerical values are explored using the text miner to collect the internet data from the web pages. In the second stage, a cluster analysis model is developed to evaluate the numerical values of the key geometric features to divide the external shapes into several groups. Several design suggestion cases can be proposed, for example, large model, mid-size model, and mini model, for designing a mobile phone. A customer preference index is developed by evaluating the numerical data of each of the key geometric features of the design suggestion cases. The design suggestion case with the top ranking of the customer preference index can be selected as the final design of the product. In this paper, an example product of a notebook computer is illustrated. It shows that the external shape of a product can be used to drive customer preferences. The presented design for customer preferences model is useful for determining a suitable external shape of the product to increase customer preferences.

Keywords: cluster analysis, customer preferences, design evaluation, design for customer preferences, product design

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Authors: Lu Ren, You-Liang Fang, Yan-Gang Zhao

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In recent years, the application of BIM (Building Information Modelling) to construction schedule plan has been the focus of more and more researchers. In order to assess the reasonable level of the BIM-based construction schedule plan, that is whether the schedule can be completed on time, some researchers have introduced reliability theory to evaluate. In the process of evaluation, the uncertain factors affecting the construction schedule plan are regarded as random variables, and probability distributions of the random variables are assumed to be normal distribution, which is determined using two parameters evaluated from the mean and standard deviation of statistical data. However, in practical engineering, most of the uncertain influence factors are not normal random variables. So the evaluation results of the construction schedule plan will be unreasonable under the assumption that probability distributions of random variables submitted to the normal distribution. Therefore, in order to get a more reasonable evaluation result, it is necessary to describe the distribution of random variables more comprehensively. For this purpose, cubic normal distribution is introduced in this paper to describe the distribution of arbitrary random variables, which is determined by the first four moments (mean, standard deviation, skewness and kurtosis). In this paper, building the BIM model firstly according to the design messages of the structure and making the construction schedule plan based on BIM, then the cubic normal distribution is used to describe the distribution of the random variables due to the collecting statistical data of the random factors influencing construction schedule plan. Next the reliability analysis of the construction schedule plan based on BIM can be carried out more reasonably. Finally, the more accurate evaluation results can be given providing reference for the implementation of the actual construction schedule plan. In the last part of this paper, the more efficiency and accuracy of the proposed methodology for the reliability analysis of the construction schedule plan based on BIM are conducted through practical engineering case.

Keywords: BIM, construction schedule plan, cubic normal distribution, reliability analysis

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Authors: Silumpa Suboonsan, Suwat Pattaramalai

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In this paper, the performance of internet usage by using Vertical Handover (VHO) between cellular network and wireless local area network (WLAN) on Silom line Bangkok Mass Transit System (BTS) is evaluated. In the evaluation model, there is the WLAN on every BTS station and there are cellular base stations along the BTS path. The maximum data rates for cellular network are 7.2, 14.4, 42, and 100Mbps and for WLAN are 54, 150, and 300Mbps. The simulation are based on users using internet, watching VDOs and browsing web pages, on the BTS train from first station to the last station (full time usage) and on the BTS train for traveling some number of stations (random time). The results shows that VHO system has throughput a lot more than using only cellular network when the data rate of WLAN is more than one of cellular network. Lastly, the number of watching HD VDO and Full HD VDO is higher on VHO system on both regular time and rush hour of BTS travelling.

Keywords: vertical handover, WLAN, cellular, silom line BTS

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Authors: Ping-Hsiung Wang, Kuo-Chun Chang

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There has been a common trend worldwide in the seismic design and evaluation of bridges towards the performance-based method where the lateral displacement or the displacement ductility of bridge column is regarded as an important indicator for performance assessment. However, the seismic response of a bridge to an earthquake is a combined result of cyclic displacements and accumulated energy dissipation, causing damage to the bridge, and hence the lateral displacement (ductility) alone is insufficient to tell its actual seismic performance. This study aims to propose a damage-based seismic design and evaluation method for reinforced concrete bridges on the basis of the newly developed capacity-based inelastic displacement spectra. The capacity-based inelastic displacement spectra that comprise an inelastic displacement ratio spectrum and a corresponding damage state spectrum was constructed by using a series of nonlinear time history analyses and a versatile, smooth hysteresis model. The smooth model could take into account the effects of various design parameters of RC bridge columns and correlates the column’s strength deterioration with the Park and Ang’s damage index. It was proved that the damage index not only can be used to accurately predict the onset of strength deterioration, but also can be a good indicator for assessing the actual visible damage condition of column regardless of its loading history (i.e., similar damage index corresponds to similar actual damage condition for the same designed columns subjected to very different cyclic loading protocols as well as earthquake loading), providing a better insight into the seismic performance of bridges. Besides, the computed spectra show that the inelastic displacement ratio for far-field ground motions approximately conforms to the equal displacement rule when structural period is larger than around 0.8 s, but that for near-fault ground motions departs from the rule in the whole considered spectral regions. Furthermore, the near-fault ground motions would lead to significantly greater inelastic displacement ratio and damage index than far-field ground motions and most of the practical design scenarios cannot survive the considered near-fault ground motion when the strength reduction factor of bridge is not less than 5.0. Finally, the spectrum formula is presented as a function of structural period, strength reduction factor, and various column design parameters for far-field and near-fault ground motions by means of the regression analysis of the computed spectra. And based on the developed spectrum formula, a design example of a bridge is presented to illustrate the proposed damage-based seismic design and evaluation method where the damage state of the bridge is used as the performance objective.

Keywords: damage index, far-field, near-fault, reinforced concrete bridge, seismic design and evaluation

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Authors: Witthaya Mekhum, Waleerak Sittisom

Abstract:

This research investigated the effect on occupational health safety and environment at work from metal handicraft using Rattanakosin local wisdom focusing on pollution, accidents, and injuries from work. The sample group in this study included 48 metal handicraft workers in 5 communities by using questionnaires and interview to collect data. The evaluation form TISI 18001 was used to analyze job safety analysis (JSA). The results showed that risk at work reduced after applying the developed model. Banbu Community produces alloy bowl rubbed with stone. The high risk process is melting and hitting process. Before the application, the work risk was 82.71%. After the application of the developed model, the work risk was reduced to 50.61%. Banbart Community produces monk’s food bowl. The high risk process is blow pipe welding. Before the application, the work risk was 93.59%. After the application of the developed model, the work risk was reduced to 48.14%. Bannoen Community produces circle gong. The high risk process is milling process. Before the application, the work risk was 85.18%. After the application of the developed model, the work risk was reduced to 46.91%. Teethong Community produces gold leaf. The high risk process is hitting and spreading process. Before the application, the work risk was 86.42%. After the application of the developed model, the work risk was reduced to 64.19%. Ban Changthong Community produces gold ornament. The high risk process is gold melting process. Before the application, the work risk was 67.90%. After the application of the developed model, the work risk was reduced to 37.03%. It can be concluded that with the application of the developed model, the work risk of 5 communities was reduced in the 3 main groups: (1) Work illness reduced by 16.77%; (2) Pollution from work reduced by 10.31%; (3) Accidents and injuries from work reduced by 15.62%.

Keywords: occupational health, safety, local wisdom, Rattanakosin

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Authors: Tesfay Gidey, Emiru Birhane, Ashenafi Manaye, Hailemariam Kassa, Tesfay Atsbha, Negasi Solomon, Hadgu Hishe, Aklilu Negussie, Petr Madera, Jose G. Borges

Abstract:

The globally endangered Dracaena ombet is one of the ten dragon multipurpose tree species in arid ecosystems. Anthropogenic and natural factors are now impacting the sustainability of the species. This study was conducted to prioritize criteria and alternative strategies for the conservation of the species using the analytical hierarchy process (AHP) model by involving all relevant stakeholders in the Desa'a dry Afromontane forest in northern Ethiopia. Information about the potential alternative strategies and the criteria for their evaluation was first collected from experts, personal experiences, and literature reviews. Afterward, they were validated using stakeholders' focus group discussions. Five candidate strategies with three evaluation criteria were considered for prioritization using the AHP techniques. The overall priority ranking value of the stakeholders showed that the ecological criterion was deemed as the most essential factor for the choice of alternative strategies, followed by the economic and social criteria. The minimum cut-off strategy, combining exclosures with the collection of only 5% of plant parts from the species, soil and water conservation, and silviculture interventions, was selected as the best alternative strategy for sustainable D. ombet conservation. The livelihood losses due to the selected strategy should be compensated by the collection of non-timber forest products, poultry farming, home gardens, rearing small ruminants, beekeeping, and agroforestry. This approach may be extended to study other dragon tree species and explore strategies for the conservation of other arid ecosystems.

Keywords: conservation strategies, analytical hierarchy process model, Desa'a forest, endangered species, Ethiopia, overexploitation

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Authors: Isiaka Oladele Oladipo, Olusegun Adewale Ajayi

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The blood pressure fitness of female college students has been implicated in sedentary lifestyles. This study was designed to determine the effects of the Aerobic Dance Circuit Training Programme (ADCT) on blood pressure variables (Diastolic Blood Pressure (DBP) and Systolic Blood Pressure (SBP). Participants’ Pretest-Posttest control group quasi-experimental design using a 2x2x4 factorial matrix was adopted, while one (1) research question and two (2) research hypotheses were formulated. Seventy (70) untrained obese students-volunteers age 21.10±2.46 years were purposively selected from Oyo town, Nigeria; Emmanuel Alayande College of Education (experimental group and Federal College of Education (special) control group. The participants’ BMI, weight (kg), height (m), systolic bp(mmHg), and diastolic bp (mmHg) were measured before and completion of ADCT. Data collected were analysed using a pie chart, graph, percentage, mean, frequency, and standard deviation, while a t-test was used to analyse the stated hypotheses set at the critical level of 0.05. There were significant mean differences in baseline and post-treatment values of blood pressure variables in terms of SBP among the experimental group 136.49mmHg and 131.66mmHg; control group 130.82mmHg and 130.56mmHg (crit-t=2.00, cal.t=3.02, df=69, p<.0, the hypothesis was rejected; while DBP experimental group 88.65mmHg and 82.21mmHg; control group 69.91mmHg and 72.66mmHg (crit-t=2.00, cal.t=1.437, df=69, p>.05) in which the hypothesis was accepted). It was revealed from the findings that participants’ SBP decrease from week 4 to week 12 of ADCT indicated an effective reduction in blood pressure variables of obese female students. Therefore, the study confirmed that the use of ADCT is safe and effective in the management of blood pressure for the healthy benefit of obesity.

Keywords: aerobic dance circuit training, fitness lifestyles, obese college female students, systolic blood pressure, diastolic blood pressure

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Authors: Hyunsang Kim, Younghun Kim, Younghee Kim, Sangku Lee

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We investigated ecotoxicity and performed an experiment for removing ZnO nanoparticles in water. Short-term exposure of hatching test using fertilized eggs (O. latipes) showed deformity in 5 ppm of ZnO nanoparticles solution, and in 10ppm ZnO nanoparticles solution delayed hatching was observed. Herein, chemical precipitation method was suggested for removing ZnO nanoparticles in water. The precipitated ZnO nanoparticles showed the form of ZnS after addition of Na2S, and the form of Zn3(PO4)2 for Na2HPO4. The removal efficiency of ZnO nanoparticles in water was closed to 100% for two case. In ecotoxicity evaluation of as-precipitated ZnS and Zn3(PO4)2, they did not cause any acute toxicity for D. magna. It is noted that this precipitation treatment of ZnO is effective to reduce the potential cytotoxicity.

Keywords: ZnO nanopraticles, ZnS, Zn3(PO4)2, ecotoxicity evaluation, chemical precipitation

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Authors: Xueqing Ivy Chen, Christo De Coning

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It is clear from practice that a gap exists between Result-Based Monitoring and Evaluation (RBME) as a discipline, and Knowledge Management (KM) on the other hand. Whereas various government departments have institutionalised these functions, KM and M&E has functioned in isolation from each other in a practical sense in the public sector. It’s therefore necessary to explore the relationship between KM and M&E and the necessity for integration, so that a convergence of these disciplines can be established. An integration of KM and M&E will lead to integration and improvement of evidence-based information and policy decision-making. M&E and KM process models are available but the complementarity between specific process steps of these process models are not exploited. A need exists to clarify the relationships between these functions in order to ensure evidence based information and policy decision-making. This paper will depart from the well-known policy process models, such as the generic model and consider recent on the interface between policy, M&E and KM.

Keywords: result-based monitoring and evaluation, RBME, knowledge management, KM, evident based decision making, public policy, information systems, institutional arrangement

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Authors: Ting Hsiang Chang

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Nowadays in Taiwan, higher education, which was previously more emphasized on teaching-oriented approaches, has gradually shifted to an approach more focusing on students learning outcomes. With student employment rate as an important indicator for University Program Evaluation periodically held by the Ministry of Education, it becomes extremely critical for a university to build up a teaching and learning quality assurance system to bridge the gap between learning and practice. Teaching and Learning Quality Assurance System has been built and implemented at Chaoyang University of Technology for years and has received substantial results. By employing various forms of evaluation and performance appraisals, the effectiveness of teaching and learning can consistently be tracked as a means of ensuring teaching and learning quality. This study aims to explore the evaluation system of teaching and learning quality assurance system at the Chaoyang University of Technology by means of content analysis. The study contents the evaluation reports on the teaching and learning quality assurance at the Chaoyang University of Technology in the Academic Year 2013-2015. The quantitative results of the assessment were analyzed using the five-point Likert Scale. Quality assurance Committee meetings were further held for examining and discussions on the results. To the end, the annual evaluation report is to be produced as references used to improve approaches in both teaching and learning. The findings indicate that there is a respective relationship between the overall teaching evaluation items and the teaching goals and core competencies. In addition, graduates’ feedbacks were also collected for further analysis to examine if the current educational planning is able to achieve the university’s teaching goal and cultivation of core competencies.

Keywords: core competencies, teaching and learning quality assurance system, teaching goals, university program evaluation

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Authors: Mohammed Makki, Milad Showkatbakhsh, Aiman Tabony

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Computational applications of natural evolutionary processes as problem-solving tools have been well established since the mid-20th century. However, their application within architecture and design has only gained ground in recent years, with an increasing number of academics and professionals in the field electing to utilize evolutionary computation to address problems comprised from multiple conflicting objectives with no clear optimal solution. Recent advances in computer science and its consequent constructive influence on the architectural discourse has led to the emergence of multiple algorithmic processes capable of simulating the evolutionary process in nature within an efficient timescale. Many of the developed processes of generating a population of candidate solutions to a design problem through an evolutionary based stochastic search process are often driven through the application of both environmental and architectural parameters. These methods allow for conflicting objectives to be simultaneously, independently, and objectively optimized. This is an essential approach in design problems with a final product that must address the demand of a multitude of individuals with various requirements. However, one of the main challenges encountered through the application of an evolutionary process as a design tool is the ability for the simulation to maintain variation amongst design solutions in the population while simultaneously increasing in fitness. This is most commonly known as the ‘golden rule’ of balancing exploration and exploitation over time; the difficulty of achieving this balance in the simulation is due to the tendency of either variation or optimization being favored as the simulation progresses. In such cases, the generated population of candidate solutions has either optimized very early in the simulation, or has continued to maintain high levels of variation to which an optimal set could not be discerned; thus, providing the user with a solution set that has not evolved efficiently to the objectives outlined in the problem at hand. As such, the experiments presented in this paper seek to achieve the ‘golden rule’ by incorporating a mathematical fitness criterion for the development of an urban tissue comprised from the superblock as its primary architectural element. The mathematical value investigated in the experiments is the standard deviation factor. Traditionally, the standard deviation factor has been used as an analytical value rather than a generative one, conventionally used to measure the distribution of variation within a population by calculating the degree by which the majority of the population deviates from the mean. A higher standard deviation value delineates a higher number of the population is clustered around the mean and thus limited variation within the population, while a lower standard deviation value is due to greater variation within the population and a lack of convergence towards an optimal solution. The results presented will aim to clarify the extent to which the utilization of the standard deviation factor as a fitness criterion can be advantageous to generating fitter individuals in a more efficient timeframe when compared to conventional simulations that only incorporate architectural and environmental parameters.

Keywords: architecture, computation, evolution, standard deviation, urban

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Authors: Fally Titikpina, Abderafi Charki, Antoine Caucheteux, David Bigaud

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The building sector is one of the largest energy consumer with about 40% of the final energy consumption in the European Union. Ensuring building energy performance is of scientific, technological and sociological matter. To assess a building energy performance, the consumption being predicted or estimated during the design stage is compared with the measured consumption when the building is operational. When valuing this performance, many buildings show significant differences between the calculated and measured consumption. In order to assess the performance accurately and ensure the thermal efficiency of the building, it is necessary to evaluate the uncertainties involved not only in measurement but also those induced by the propagation of dynamic and static input data in the model being used. The evaluation of measurement uncertainty is based on both the knowledge about the measurement process and the input quantities which influence the result of measurement. Measurement uncertainty can be evaluated within the framework of conventional statistics presented in the \textit{Guide to the Expression of Measurement Uncertainty (GUM)} as well as by Bayesian Statistical Theory (BST). Another choice is the use of numerical methods like Monte Carlo Simulation (MCS). In this paper, we proposed to evaluate the uncertainty associated to the use of a simplified model for the estimation of the energy consumption of a given building. A detailed review and discussion of these three approaches (GUM, MCS and BST) is given. Therefore, an office building has been monitored and multiple sensors have been mounted on candidate locations to get required data. The monitored zone is composed of six offices and has an overall surface of 102 $m^2$. Temperature data, electrical and heating consumption, windows opening and occupancy rate are the features for our research work.

Keywords: building energy performance, uncertainty evaluation, GUM, bayesian approach, monte carlo method

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Authors: Reza Mohammadzadeh

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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

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